Space-Based Integrated Multi-Sensor System for CSO Discrimination and Identification (SBIMSS for CSODI)

This Phase I proposal identifies the key system requirements for an integrated space based multi-sensor space surveillance system capable of mission critical target tracking, discrimination, and identification (TDI) against closely spaced objects (CSO). In the proposed concept a set of visible and IR sensors track CSOs and provides a prioritized location map for an active laser tracking unit, which is then used to interrogate CSO and extract information for their discrimination and detection of threat cloud (threat/ non-threat). Multi-mode/modality images and data of CSO can be presented at various signal levels to simulate a typical engagement timeline. Active detection technology enables system to operate in both day and night and for “dark pass” tracking of satellites through the Earth’s shadow, adding means for optical signal gating, which can greatly enhance the signal-to-noise ratio in an acquired data. During Phase I we will design and integrate the proof of concept testbed to demonstrate TDI feasibility on targets that imitate CSO. During Phase II, we will extend the performance capabilities of the proposed system, design and build a breadboard for verifying and optimizing the predicted system performance, demonstrate and refine laboratory operation, and estimate the working envelope. BENEFIT: An important benefit of the proposed concept is to leverage the capability of existing and advanced sensors by integrating the data produced by all of them to improve significantly the image information content beyond that produced by any one of them. The most immediate application is to surveillance systems that employ multiple sensors. The technologies developed under this effort can be applied to various air and space surveillance systems against fast moving, closely-spaced airplanes, missiles and space objects. In commercial sector this technology can be applied to air security and air-traffic control, astronomy, navigation systems and other areas where concurrent detection and discrimination of multiple objects is essential. Likewise, the methods should be extendable to commercial inspection systems that employ multiple sensors.